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Found 4 papers, 3 papers with code
Insights from the Use of Previously Unseen Neural Architecture Search Datasets
The boundless possibility of neural networks which can be used to solve a problem -- each with different performance -- leads to a situation where a Deep Learning expert is required to identify the best neural network.
SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics
Neural Architecture Search (NAS) algorithms are intended to remove the burden of manual neural network design, and have shown to be capable of designing excellent models for a variety of well-known problems.
TrustyAI Explainability Toolkit
TrustyAI is an initiative which looks into explainable artificial intelligence (XAI) solutions to address this issue of explainability in the context of both AI models and decision services.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners
One-shot Neural Architecture Search (NAS) aims to minimize the computational expense of discovering state-of-the-art models.
Ranked #39 on
Neural Architecture Search
on CIFAR-10
